Messages Ranking in Social Network

摘要：

　　Nowadays,people engage more and more in social networks,such as Twitter,FaceBook,and Orkut,etc.In these social network sites,users create relationship with familiar or unfamiliar persons and share short messages between each other.One arising problem for these social networks is information is real-time and updates so quickly that users often feel lost in such huge information flow and struggle to find what really interest them.In this paper,we study the problem of personalized ranking in social network and use the SSRankBoost algorithm,a kind of pairwise learning to rank method to solve this problem.We evaluate our approach using a real microblog dataset for experiment and analyze the result empirically.The result shows clear improvement compared to those without ranking criteria,abstract environment.

关键词： ranking social network microblog

作者: Bo Li Fengxian Shi Enhong Chen

作者单位: University of Science and Technology of China,China

会议类型: 国际会议

会议名称: 7th IFIP TC 12 International Conference (第七届智能信息处理国际会议 (IIP 2012))

会议地点: 桂林

会议语种:英文

页码: 268-275

在线出版日期: 2012-10-12（万方平台首次上网日期，不代表论文的发表时间）